Texture-Based Image Retrieval for Computerized Tomography Databases

In this paper we propose a CBIR system for retrieval ofnormal anatomical regions present in Computed Tomography studies of the chest and abdomen. We implement and compare eight similarity measures using local and global co-occurrence texture descriptors. The preliminary results are obtained using a CT database consisting of 344 CT images representing the segmented heart and great vessels, liver, renal and splenic parenchyma, and backbone from two different patients. We evaluate the results with respect to the retrieval precision metric for each of the similarity measures when calculated at both levels, per organ and overall.

• Type: Conference
• Year: 2005
• Where: CBMS
• Authors: Winnie Tsang, Andrew Corboy, Ken Lee, Daniela Stan Raicu, Jacob D. Furst
• Keywords: CBMS 2005, Co-occurrence Texture Descriptors, Computed Tomography Studies, Medical Imaging, Similarity Measures